Findings
Clinical trials often have unmet measurement needs, where traditional endpoints may not adequately characterize disease progression, treatment response, or new disease phenotypes.
Traditional trial designs can create a high patient burden, which can negatively impact the adoption of new measures by both clinicians and patients.
Clinical trials face significant operational challenges, including the risk of disruption, slow enrollment, poor medication adherence, and difficulty making early go/no-go decisions.
There is a need to improve the predictability rates for advancing new products from early-phase trials to pivotal trials.

Recommendations
Select digital measures to address specific unmet needs, such as to increase sensitivity in detecting disease worsening, characterize treatment response in subpopulations, or identify new disease phenotypes.
Prioritize digital measures that are well-received by clinicians and patients by demonstrating lower patient burden and higher patient relevance.
Deploy digital measures to improve trial efficiency and speed by reducing dependence on clinic visits, enabling earlier go/no-go decisions with higher resolution data, or improving medication adherence.
Use digital measures in early-phase trials to improve the probability of success for advancing new products to pivotal trials.
Consider digital measures that provide remote, continuous physiological insight to enable better oversight and remote management of trial participants.

Regulatory Considerations
When selecting a digital endpoint, a key consideration is whether the measure will increase the likelihood of regulatory approval or support a broader label claim.
A digital measure can strengthen a regulatory submission by generating more complete and patient-centric information that demonstrates the benefit of a new therapy.